Mining of Self-Regulated Learning Process Model in Online Environment

The COVID-19 pandemic has necessitated a swift transition from traditional classrooms to fully online learning, prompting the education system to prioritize the maintenance and enhancement of education quality, particularly at the elementary level. In ensuring students' ability to self-regulate their learning, it is crucial for them to develop independence and responsibility in acquiring new knowledge, as this will impact their educational progress in higher levels. This study proposes the application of process mining, specifically using the web-based system called GoSRL to map students' SRL behaviors to activities within the Moodle online learning platform. While typically employed in business process analytics, process mining can also be utilized for learning analytics, as indicated by recent research. Adopting the Process Mining Project Methodology (PM2), this research investigates and carries out online SRL process model discovery by employing various processes, such as data processing, mining, analysis, and evaluation. Through extraction of records from the Moodle event log, encompassing the online activities of the students, SRL process models are generated. The final outcome of this project is a web-based system design that equips teachers with insights into students' online SRL, thereby facilitating a better understanding of their learning processes and enabling improvements in the quality of teaching and learning systems.